The present disclosure relates to mobile application diagnostics, and more specifically, diagnosing an unfavorable mobile application user experience.
Many consumers prefer mobile applications (“apps”) over a mobile version of websites. Smart phone users often respond quickly when it comes to evaluating the usefulness of a downloaded app. Many users may download the app from an application marketplace, try it, and if they find it unusable, not user-friendly, or the app does not serve their purpose they will immediately uninstall. Most business enterprises prefer that users be engaged with their enterprise-specific customized apps. Downloading an app and then quickly uninstalling not only lowers the user experience rating of the app but may also impact the business reputation of a company.
Understanding the root causes that eventually lead a user to uninstall an app may be of interest to business enterprises. There exists a long-felt need for systems and methods that provide an understanding of path(s) to an unfavorable application event (e.g., uninstall), which may facilitate the refinement process and increase the likelihood of customer satisfaction. Application rankings or customer feedback in the application marketplace may provide some insight to app developers with respect to user experience. However, user-initiated feedback processes can be subjective and may not provide all the information necessary to make required adjustments to the application. For example, a group of users may complain online about slow performance, but they may not give details about the area of the application that has caused dissatisfaction. Secondly, users may not take the time to provide feedback, and thus, the enterprise may not be aware that a problem exists. It may be beneficial to provide systems and methods for collecting definitive and quantitative usage information on key events that precede a user uninstallation of an app.